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Intratumoral heterogeneity analysis reveals hidden associations between protein expression losses and patient survival in clear cell renal cell carcinoma

机译:肿瘤内异质性分析揭示了透明细胞肾细胞癌中蛋白质表达损失与患者存活之间的隐藏关联

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摘要

Intratumoral heterogeneity (ITH) is a prominent feature of kidney cancer. It is not known whether it has utility in finding associations between protein expression and clinical parameters. We used ITH that is detected by immunohistochemistry (IHC) to aid the association analysis between the loss of SWI/SNF components and clinical parameters.160 ccRCC tumors (40 per tumor stage) were used to generate tissue microarray (TMA). Four foci from different regions of each tumor were selected. IHC was performed against PBRM1, ARID1A, SETD2, SMARCA4, and SMARCA2. Statistical analyses were performed to correlate biomarker losses with patho-clinical parameters. Categorical variables were compared between groups using Fisher's exact tests. Univariate and multivariable analyses were used to correlate biomarker changes and patient survivals. Multivariable analyses were performed by constructing decision trees using the classification and regression trees (CART) methodology. IHC detected widespread ITH in ccRCC tumors. The statistical analysis of the “Truncal loss” (root loss) found additional correlations between biomarker losses and tumor stages than the traditional “Loss in tumor (total)”. Losses of SMARCA4 or SMARCA2 significantly improved prognosis for overall survival (OS). Losses of PBRM1, ARID1A or SETD2 had the opposite effect. Thus “Truncal Loss” analysis revealed hidden links between protein losses and patient survival in ccRCC.
机译:肿瘤内异质性(ITH)是肾癌的突出特征。尚不知道它是否可用于发现蛋白质表达与临床参数之间的关联。我们使用通过免疫组织化学(IHC)检测的ITH来辅助SWI / SNF成分的丢失与临床参数之间的关联分析。160ccRCC肿瘤(每个肿瘤分期40个)用于生成组织微阵列(TMA)。从每个肿瘤的不同区域选择四个灶。针对PBRM1,ARID1A,SETD2,SMARCA4和SMARCA2执行IHC。进行统计分析以使生物标志物损失与病理临床参数相关。使用Fisher精确检验比较各组之间的分类变量。使用单变量和多变量分析来关联生物标志物变化和患者生存。通过使用分类和回归树(CART)方法构建决策树来执行多变量分析。 IHC在ccRCC肿瘤中检测到了广泛的ITH。对“ Truncal损失”(根部损失)的统计分析发现,与传统的“肿瘤损失(总)”相比,生物标志物损失与肿瘤分期之间存在其他相关性。 SMARCA4或SMARCA2的丧失显着改善了总生存期(OS)的预后。 PBRM1,ARID1A或SETD2的丢失产生相反的影响。因此,“ Truncal Loss”分析揭示了ccRCC中蛋白质损失与患者生存之间的隐藏联系。

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